System for providing extensible location-based services

ABSTRACT

A system for providing location-based services to a mobile device regularly determines the location of the mobile device. Using the location of the device, the system queries a database of virtual geographic regions to determine if the location of the mobile device falls within one or more of the virtual geographic regions. The virtual geographic regions correspond to service entities that have purchased, rented, leased, or otherwise acquired the virtual geographic regions. The virtual geographic regions cover a certain area of a map. If the mobile device is within a virtual geographic region, the system notifies the mobile device. A location-based services application installed on the mobile device launches an applet for the entity that acquired the virtual geographic region within which the mobile device is located. When the mobile device is located within multiple overlapping virtual geographic regions, the system generates a prioritization scheme that defines which of the corresponding service entities should be displayed on the mobile device, and in what order the service entities should be displayed.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No. 13/420,431, filed on Mar. 14, 2012 and U.S. application Ser. No. 14/732,081, filed on Jun. 5, 2015, the disclosure of which are expressly incorporated herein by reference in their entirety.

BACKGROUND Technical Field

This application relates to mobile applications. In particular, this application relates to a system for providing extensible location-based services to a mobile device.

BRIEF DESCRIPTION OF THE DRAWINGS

The system may be better understood with reference to the following drawings and description. The elements in the figures are not necessarily to scale, emphasis instead being placed upon illustrating the principles of the type model. In the figures, like-referenced numerals designate corresponding features throughout the different views.

FIG. 1 shows an example of an architecture for providing an extensible location-based services to a mobile device.

FIG. 2 shows examples of virtual geographic regions that are defined as circles.

FIG. 3 shows examples of virtual geographic regions that are defined as polygons.

FIG. 4 shows an example of an applet interface displayed by the location-based mobile application installed on a mobile device.

FIGS. 5-7 show another example of an applet launched on a mobile device.

FIG. 8 is an example of process a location-based services system may implement for providing location-based services to a mobile device.

FIG. 9 shows a mobile device displaying an applet window that includes multiple service entities.

FIG. 10 shows a mobile device displaying an applet window that may be displayed when the mobile device is not located within a virtual geographic region.

DETAILED DESCRIPTION

FIG. 1 shows an example of an architecture 100 for providing an extensible location-based services to a mobile device. The architecture 100 includes a mobile device 102 equipped with a location-based service application, a location-based services system 104, a location-based services database 106, and service entities 108, 110, 112, each of which may communicate via a communications network 114. The mobile device 102 may be a cellular phone, tablet, smart phone, PDA or other mobile communication device configured to access the internet. The mobile device 102 has installed thereon a location-based services application configured to communicate with the system 104.

The communications network 114 may be any private or public communications network or combination of networks. The communications network 114 may be configured to couple a computing device, such as a server, system, database, or other network enabled device, to another device to enable communication of data between computing devices. The communications network 114 may generally be enabled to employ any form of computer-readable media for communicating information from one computing device to another. The communications network 114 may include one or more of a wireless network, a wired network, a local area network (LAN), a wide area network (WAN), a direct connection such as through a Universal Serial Bus (USB) port, and the like, and may include the set of interconnected networks that make up the Internet. The communications network 114 may include any communication method by which information may travel between computing devices.

The service entities 108, 110, 112 each correspond to a vender of goods or services that purchased, rented, leased, or otherwise acquired virtual geographic regions from the provider of the location-based services system. The database 106 may store data corresponding to the virtual geographic region(s) of each service entity 108, 110, 112. The mobile device 102 transmits location data to the system 104 via the communications network. Based on the location data, the system 104 determines whether the location of the mobile device 102 falls in the proximity of the virtual geographic region of one or more of the service entities 108, 110, 112. If the location of the mobile device 102 falls in the proximity of the virtual geographic region of one of the service entities 108, 110, 112, the system 104 notifies the location-based services application installed on the mobile device 102. The application launches an applet corresponding to the identified service entity. The applet may access and load HTML-based pages corresponding to the identified service entity, which may provide sales information, product lists, coupons, a map of a nearby store, phone number, hours of operation, and other information corresponding to the service entity.

If the location of the mobile device 102 falls in the proximity of the virtual geographic regions of multiple service entities 108, 110, 112, the system 104 may execute a conflict resolution process to determine the multiple service entity about which to notify the mobile device 102. In another example, the application may be configured to display a menu to a user that prompts the user to select which of the identified service entity applets to launch. In this example, the conflict resolution process may include a determination of what order to list the identified multiple service entities on the menu, or whether to omit any of the identified service entities from the menu.

If the location of the mobile device 102 does not fall within the proximity of the virtual geographic region of any service entity, the system 104 may determine whether there are any service entities corresponding to nearby virtual geographic region about which to notify the user of the mobile device 102.

FIGS. 2-3 show a map 200 including examples of virtual geographic regions that may be purchased, rented, leased, or otherwise acquired by a service entity. FIG. 2 shows examples of virtual geographic regions 202 and 204 that are defined as circles. In particular, the geographic regions 202 and 204 may be defined by a geographic coordinate (e.g., longitude and latitude) and a radius. In FIG. 2 region 204 is defined by a larger radius than region 202.

FIG. 3 shows examples of virtual geographic regions 302 and 304 that are defined as polygons. The polygons may be defined by geographic coordinates. For example, six geographic coordinates may form a six sided polygon region. Borders of the virtual geographic regions may also be defined, partly or wholly, by pre-defined geographic regions such as a zip code, city limit, etc. The virtual geographic region may be defined by a combination of the above examples as well.

The boundaries of the virtual geographic regions may be defined by the service entity purchasing, renting or leasing the region. For example, the service entity may select the geographic coordinate and radius defining their circular virtual geographic region, or may select the geographic coordinates defining the polygonal virtual geographic region. Monetization of the virtual geographic regions may be based on area as well as location. For example, a region covering more area may cost more than a smaller region. As another example, a region in a densely populated area may cost more than a region of the same size in a less populated area.

Virtual geographic regions corresponding to different service entities may overlap. When a mobile device enters an area covered by multiple virtual geographic regions, the location-based services system may perform conflict resolution, which is discussed in more detail below. In addition, a service entity may also purchase exclusive rights to a particular virtual geographic region.

FIG. 4 shows an example of an applet interface 400 displayed by the location-based mobile application installed on a mobile device 402. In this example the mobile device 402 was determined to be within a virtual geographic region corresponding to a coffee shop. The location-based services system notifies the application installed on the mobile device 402 that the device 402 is within the identified virtual geographic region and launces the applet and displays the applet interface 400 corresponding to the coffee shop. The display 402 may be an initial applet window displayed when the corresponding applet is launched. The initial applet window provides the user includes menu items 404, 406 and 408. The applet may allow the user to view the menu (menu item 406) and place an order. The applet may allow the user of the mobile device 402 to order the usual (menu item 404). The applet may collect purchasing data about the user's purchases at this coffee shop, or at coffee shops in general to determine what order to place when the user clicks on the “Order the Usual” menu item 404. In another example, the applet may allow the user to manually input a product that is purchased when the user clicks on the menu item 404. The applet may also allow the user to determine what music is playing in the corresponding coffee shot (menu item 408).

FIGS. 5-7 show another example of an applet launched on a mobile device 500. In this example the mobile device 500 is determined to be within a virtual geographic region corresponding to an electronics store. FIG. 500 shows that the subsequently launched applet may provide a layout 502 of the nearby retail store. FIG. 6 shows that the applet may overlay a sales or promotion indicator 602 over the layout. The indicator 602 may indicate a location within the store of a sale or promotion. If the user selects the indicator 602, the applet may display a sale or promotion window 702, as shown in FIG. 7. The applet may integrate with the electronics store's website to enable the user to make purchases from the retail store using the applet.

FIG. 8 is an example of process 800 a location-based services system may implement for providing location-based services to a mobile device. The disclosed methods, processes, programs, and/or instructions may be encoded in a signal-bearing medium, a computer-readable medium such as a memory, programmed within a device such as on one or more integrated circuits, or processed by a controller or a computer processor. If the methods are performed by software, the software may reside in a memory resident to or interfaced to a communication interface, or any other type of non-volatile or volatile memory. The memory may include an ordered listing of executable instructions for implementing logical functions. A logical function may be implemented through digital circuitry, through source code, through analog circuitry, or through an analog source such as that occurring through an analog electrical, audio, or video signal. The software may be embodied in any computer-readable or signal-bearing medium, for use by, or in connection with, an instruction executable system, apparatus, or device. Such a system may include a computer-based system, a processor-containing system, or another system that may selectively fetch instructions from an instruction executable system, apparatus, or device that may also execute instructions.

The system receives location data from a mobile device equipped with a location-based services application (step 802). The location data may be geographic coordinates (e.g., longitude and latitude), identification of a geographic sector in which the mobile device is located, identification of the nearest base station, coordinates determined via triangulation, or other location data corresponding to other known mobile device location techniques.

Based on the location data, the system determines whether the location of the mobile device is within the virtual geographic region purchased, rented, leased, or otherwise acquired by a subscribing service entity (step 804). The system may compare the location of the mobile device with the virtual geographic regions stored in a database to determine whether the mobile device location falls within the virtual geographic region. If the system determines that the mobile device is not within a virtual geographic region, the system determines whether there are other, nearby virtual geographic regions that might be of interest to the user of the mobile device (step 806). The system may, for example, notify the application installed on the mobile device of the next closest virtual geographic region. The system may also compare the distance between the next closest virtual geographic region against a threshold, such that the system will not notify the application of the next closest virtual geographic region if the virtual geographic region is greater than a threshold distance (e.g., 5 miles, 25 miles, etc.) from the location of the mobile device.

The system may determine that, as another example, based on the direction of the mobile device, the mobile device is approaching a particular virtual geographic region and the system may notify the application installed on the mobile device to launch the corresponding applet even before the mobile device passes into the virtual geographic region.

If the system determines that there no other, nearby virtual geographic regions about which to notify the application, the application does not launch an applet and the system continues to obtain new location data of the mobile device (step 802). If the system determines that there are other, nearby virtual geographic regions about which to notify the application, the system transmits a notification to the application (step 808). The notification may include an identification of the corresponding service entity or other information that allows the application to know which applet to launch.

If in step 804 the system determines that location of the mobile device falls within at least one virtual geographic region, the system notifies application in the case where the system identifies a one virtual geographic region (step 810). In the case where the system identifies multiple virtual geographic regions corresponding to the location of the mobile device, such as in the case of overlapping virtual geographic regions, the system executes conflict resolution procedures (step 812).

To resolve a conflict, the system may determine the service entities (corresponding to each of the multiple virtual geographic regions) about which to notify the mobile application, as well as prioritize the service entities. Conflict resolution may be based on the location data, directional data (indicating the direction of movement of the mobile device), behavioral data about the user of the mobile device, temporal data (e.g., the time of day), and user preferences.

If the location of the mobile device falls within two overlapping virtual geographic regions, for example, the system may prioritize the virtual geographic region that the mobile device is moving towards above the virtual geographic region that the device is moving from. The movement or direction data may be received from the mobile device, or may be calculated by the system based on the current location and immediately preceding locations of the mobile device.

Prioritization of the multiple virtual geographic regions may also be based on behavioral data. The system may collect behavioral data corresponding to the mobile device and store the behavioral data in the database. Behavioral data may include, as examples, purchasing history, location history, temporal data such as the types of purchases the user makes at different times of the day or on different days of the week. If, for example, the mobile device is located within the vicinity of a coffee shop and a restaurant, the system may determine based on the behavioral data that the user of the mobile device typically visits coffee shops in the morning and restaurants in the early afternoon. Around lunch time the system may prioritize the restaurant ahead of the coffee shop, whereas the system may prioritize the coffee shop ahead of the restaurant in the morning. Thus, the system may provide different prioritization schemes based on the time of day.

Prioritization may also be based on user preferences. The application may allow the user to enter preferences in regards to the types of services entities he/she prefers (e.g., a preference of a certain restaurant chain over another, etc). The mobile device may transmit the user preferences to the system, which may be stored in the database.

The system may use a log of locations and “dwell time” to generate the prioritization scheme, indicating which of the corresponding service entities will likely be important to the user of the mobile device. One method that may be used to “score” each service entity is to sum all historical location data points using “time at location” (T) divided by “distance from nearest entity” (D_(X)), or

${{Score}_{X} = {\sum\frac{T}{D_{X}}}},$ where Score_(X) corresponds to a score for a given entity (X). In other words, for each location data point over some previous period of time, the divides the amount spent at a location divided by the distance to the nearest entity from the location data point. In this manner, a particular entity would have a higher score where the user has a longer time at the location, and would have a lower score where the user visited locations that were a greater distance from the nearest entity being scored. The system may generate a corresponding score for each of the overlapping service entities. The score generated by the above-mentioned sum may indicate which service entity the user is most likely to be interested in.

The system may use probability curve data based on the behavior data. The probability function P_(X) may correspond to, for example, a distribution curve indicating the number of times the user visited a particular entity and the time of day. If a mobile device is near a restaurant and a coffee shop, the system may also rank or prioritize the entities according to the following function: Rank_(X)=V_(X)*P_(X)(t)+S_(X), where V_(X) corresponds to the number of visits, P_(X)(t) corresponds to probability function at a given time and S_(X) corresponds to the entity score referenced above.

In addition, an amount of actions the user takes with reference to a given service entity (X) may corresponds to a utility score (U_(X)), augmenting the above function in the following manner: Rank_(X)=U_(X)*V_(X)*P_(X)(t)+S_(X). Further, as discussed above, a direction of travel of the mobile device may help determine intent of the user, such that the function may be further augmented as follows: Rank_(X)=(U_(X)*V_(X) P_(X)(t)+S_(X)) dot(Dir, D_(x)). In this manner, U_(X) accounts for the utility of a service entity, V_(X) accounts for repeated use of a service entity, P_(X) accounts for the usefulness of a service entity at a given time, S_(X) accounts for overall behavior, dot(Dir, D_(X)) accounts for direction.

Once prioritized, the system notifies application of the corresponding service entities, along with the prioritization scheme (step 814). The system is described herein as being separate from the mobile device. However, in another embodiment identification of nearby virtual geographic regions and prioritization in the case of multiple overlapping virtual geographic regions may be performed by the mobile application, taking advantage of the processing and memory capabilities of the mobile device. In this embodiment, the mobile device, after determining its location, may query the database directly to determine whether the location data corresponds to a virtual geographic region purchased, rented, leased, or otherwise acquired by a service entity. Based on the results of the query, and in the case of overlapping virtual geographic regions, the mobile application itself may be programmed to determine the prioritization scheme as discussed above. In this example the location-based services system includes the mobile device.

FIG. 9 shows a mobile device 900 displaying an applet window 902 that includes multiple service entities, including airport services 904, airline services 906, coffee shops 908, and fast food 910. The order the services entities are listed in the applet window 902 may be based on the prioritization scheme determined by the system. Prioritization may also include grouping related service entities together. For example, if the mobile device is located within the virtual geographic region of multiple fast food service entities, the prioritization scheme may group the fast food service entities together such that if the user selects the “Fast Food” option 910, a submenu is displayed that lists each of the corresponding fast food service entities. As the mobile device 900 moves, it may pass outside of one of the virtual geographic regions. As the location-based mobile application periodically updates the location of the mobile device and transmits the updated location to the system, the system may determine that the virtual geographic regions within which the mobile device is located has changed. The system generates a new prioritization scheme and transmits the new prioritization scheme along with an identification of the corresponding service entities to the mobile device. Upon receipt of the updated data, the mobile application updates the applet window 902 of the mobile device 900. In other words, as the mobile device 900 moves in and out of different virtual geographic regions, the mobile application may automatically update the applet window accordingly. In this manner, as the user walks, for example, through an airport, the list of service entities displayed on the applet window 902 may change. The changes may include addition or removal of the listed service entities, as well as a reordering of the listed service entities, as the mobile device changes location.

FIG. 10 shows a mobile device 1000 displaying an applet window 1002 that may be displayed when the mobile device is not located within a virtual geographic region. The applet window 1002 includes two options including “My Lists” 1004 and “Find Services” 1006. The “My Lists” option 1004 may include a list of default applets selected by the user, or determined by the system based on user behavior (e.g., service entities most frequented by the user). The “Find Services” option 1006 may allow the user to see applets corresponding to services that may not be tagged to any specific geographic location (e.g., taxis, social apps, internet retailers, etc).

Exemplary aspects, features, and components of the system are described above. However, the system may be implemented in many different ways. For example, although some features are shown stored in computer-readable memories (e.g., as logic implemented as computer-executable instructions or as data structures in memory), all or part of the system and its logic and data structures may be stored on, distributed across, or read from other machine-readable media. The media may include hard disks, floppy disks, CD-ROMs, a signal, such as a signal received from a network or received over multiple packets communicated across the network.

The system may be implemented with additional, different, or fewer components. As one example, a processor may be implemented as a microprocessor, a microcontroller, a DSP, an application specific integrated circuit (ASIC), discrete logic, or a combination of other types of circuits or logic. As another example, memories may be DRAM, SRAM, Flash or any other type of memory. The processing capability of the system may be distributed among multiple components, such as among multiple processors and memories, optionally including multiple distributed processing systems. Parameters, databases, and other data structures may be separately stored and managed, may be incorporated into a single memory or database, may be logically and physically organized in many different ways, and may implemented with different types of data structures such as linked lists, hash tables, or implicit storage mechanisms. Logic, such as programs or circuitry, may be combined or split among multiple programs, distributed across several memories and processors, and may be implemented in a library, such as a shared library (e.g., a dynamic link library (DLL)). The DLL, for example, may store code that prepares intermediate mappings or implements a search on the mappings. As another example, the DLL may itself provide all or some of the functionality of the system, tool, or both.

While various embodiments of the invention have been described, it will be apparent to those of ordinary skill in the art that many more embodiments and implementations are possible within the scope of the invention. Accordingly, the invention is not to be restricted except in light of the attached claims and their equivalents. 

What is claimed is:
 1. A computer-implemented method comprising: receiving, at a computer system, location information for a mobile computing device that is associated with a user; identifying, by the computer system and based, at least in part, on the location information, a plurality of candidate restaurants to be used for requests from the mobile computing device; determining, by the computer system, distances between a current location of the mobile computing device to locations for the plurality of candidate restaurants; selecting, by the computer system, historical behavior data for the user with regard to the plurality of candidate restaurants, wherein the historical behavior data identifies the user's previous interactions with each of the plurality of candidate restaurants; detecting, by the computer system, a current time of day; identifying, by the computer system and from the historical behavior data, temporal information that indicates times of the day at which the user previously interacted with each of the plurality of candidate restaurants; identifying, by the computer system and from the temporal information, time distributions for the user's interactions with each of the plurality of candidate restaurants; determining, by the computer system, probabilities that the user is most likely of visiting each of the plurality of restaurants based on comparisons of the current time of day with the time distributions; determining, by the computer system, a plurality of scores for the plurality of candidate restaurants based, at least in part, on (i) the distances between the mobile computing device and the plurality of candidate restaurants (ii) the historical behavior data for the user with regard to the plurality of candidate restaurants, and (iii) the determined probabilities, wherein the plurality of scores indicate likelihoods that the user is currently interested in using each of the plurality of candidate restaurants; selecting, by the computer system, a particular restaurant from the plurality of candidate restaurants based, at least in part, on the plurality of scores; and causing, by the computer system, the particular restaurant to be used for requests from the mobile computing device.
 2. The computer-implemented method of claim 1, further comprising: identifying, by the computer system, quantities of interactions with each of the plurality of candidate restaurants; determining, by the computer system, weighted probabilities that the user is most likely of visiting each of the plurality of restaurants based on products of the probabilities with the quantities of interactions with each of the plurality of candidate restaurants, wherein the plurality of scores being determined further based on the determined probabilities comprises the plurality of scores being determined further based on the weighted probabilities.
 3. The computer-implemented method of claim 1, wherein the previous interactions comprise previous orders placed by the user with the plurality of candidate restaurants.
 4. The computer-implemented method of claim 1, wherein the previous interactions comprise previous instances when the user was physically located at or near the plurality of candidate restaurants.
 5. The computer-implemented method of claim 4, further comprising: identifying, by the computer system and from the historical behavior data, dwell times that indicate lengths of time that the user was physical located at or near the plurality of candidate restaurants; wherein the plurality of scores are determined further based on the dwell times.
 6. The computer-implemented method of claim 5, wherein the plurality of scores are determined based on combinations of the dwell times and the distances for each of the plurality of candidate restaurants.
 7. The computer-implemented method of claim 6, wherein the combinations comprise, for each of the plurality of candidate restaurants, an aggregate value of dwell times for a particular candidate restaurant divided by a distance between the particular candidate restaurant and the mobile computing device.
 8. The computer-implemented method of claim 1, further comprising: determining, by the computer system and based on the location information, a direction that the mobile computing device is travelling, wherein the plurality of scores are determined further based on the direction that the mobile computing device is travelling.
 9. The computer-implemented method of claim 8, further comprising: determining, by the computer system, dot products for each of the plurality of candidate restaurants based on (i) the direction that the mobile computing device is travelling and (ii) the distances between the mobile computing device and the plurality of candidate restaurants, wherein the plurality of scores being determined further based on the direction that the mobile computing device is travelling comprises the plurality of scores being determined further based on the dot products for each of the plurality of candidate restaurants.
 10. The computer-implemented method of claim 1, further comprising: accessing, by the computer system, restaurant preferences previously identified by the user; wherein the plurality of scores are determined further based on the restaurant preferences for the user.
 11. The computer-implemented method of claim 1, wherein the restaurant preferences comprise types of restaurants for which the user previously identified a preference.
 12. The computer-implemented method of claim 1, wherein identifying the plurality of candidate restaurants comprises: accessing, by the computer system, information that identifies geographic regions that are associated with restaurants; comparing, by the computer system, the current location of the mobile computing device with the geographic regions; and selecting, by the computer system, the plurality of candidate restaurants from among the restaurants based on the current location of the mobile computing device being located within geographic regions associated with the plurality of candidate restaurants.
 13. The computer-implemented method of claim 1, further comprising: receiving, at the computer system and from a computing device associated with one of the restaurants, a request to associated the one of the restaurants with a particular geographic region; determining, by the computer system, a price for the one of the restaurants to virtually rent the particular geographic region with the computer system; providing, to the computing device, the determined price to virtually rent the particular geographic region.
 14. The computer-implemented method of claim 13, wherein the price is determined based, at least in part, on a size of the particular geographic region.
 15. The computer-implemented method of claim 13, wherein the price is determined based, at least in part, on a density of people within the particular geographic region.
 16. A computer system comprising: one or more processors; memory storing instructions that, when executed, cause the one or more processors to: receive location information for a mobile computing device that is associated with a user; identify, based, at least in part, on the location information, a plurality of candidate restaurants to be used for requests from the mobile computing device; determine distances between a current location of the mobile computing device to locations for the plurality of candidate restaurants; select historical behavior data for the user with regard to the plurality of candidate restaurants, wherein the historical behavior data identifies the user's previous interactions with each of the plurality of candidate restaurants; detect a current time of day; identify, from the historical behavior data, temporal information that indicates times of the day at which the user previously interacted with each of the plurality of candidate restaurants; identify, from the temporal information, time distributions for the user's interactions with each of the plurality of candidate restaurants; determine probabilities that the user is most likely of visiting each of the plurality of restaurants based on comparisons of the current time of day with the time distributions; determine a plurality of scores for the plurality of candidate restaurants based, at least in part, on (i) the distances between the mobile computing device and the plurality of candidate restaurants (ii) the historical behavior data for the user with regard to the plurality of candidate restaurants, and (iii) the determined probabilities, wherein the plurality of scores indicate likelihoods that the user is currently interested in using each of the plurality of candidate restaurants; select a particular restaurant from the plurality of candidate restaurants based, at least in part, on the plurality of scores; and cause the particular restaurant to be used for requests from the mobile computing device.
 17. The computer system of claim 16, wherein the instructions, when executed, further cause the one or more processors to: identify quantities of interactions with each of the plurality of candidate restaurants; determine weighted probabilities that the user is most likely of visiting each of the plurality of restaurants based on products of the probabilities with the quantities of interactions with each of the plurality of candidate restaurants, wherein the plurality of scores being determined further based on the determined probabilities comprises the plurality of scores being determined further based on the weighted probabilities.
 18. The computer system of claim 16, wherein the previous interactions comprise previous orders placed by the user with the plurality of candidate restaurants.
 19. The computer system of claim 16, wherein the previous interactions comprise previous instances when the user was physically located at or near the plurality of candidate restaurants.
 20. The computer system of claim 19, wherein the instructions, when executed, further cause the one or more processors to: identify, from the historical behavior data, dwell times that indicate lengths of time that the user was physical located at or near the plurality of candidate restaurants; wherein the plurality of scores are determined further based on the dwell times. 